The present invention relates to a character recognition method and, more particularly, to a user-friendly alpha-numeric character recognition method.
It is known to employ a solid state TV camera in a video inspection system. For example, U.S. Pat. No. 4,344,146 to Ray E. Davis, Jr. et al, which is entitled "Video Inspection System" and is assigned to the assignee of the present application, discloses the use of such a TV camera in a high speed, real time video inspection system wherein the TV camera has at least sixteen levels of grey scale resolution. It is also known to employ a solid state TV camera in a video measuring system. For example, Ser. No. 596,842 filed Apr. 4, 1984 by Ray E. Davis, Jr. et al, now U.S. Pat. No. 4,628,553 which is entitled "Video Measuring System" and is assigned to the assignee of the present application, discloses the use of such a TV camera in a fast, efficient, user-friendly video measuring system useful for both guality control and process control. Further, it is known to employ a vidicon camera in a method and apparatus for identifying images found, for example, on a "cents off" coupon. Such a system is shown in GB No. 2,031,207A.
The present invention is a computer-based vision system having the capability of reading printed characters and enables the user to verify, sort and tabulate products quickly and accurately. The system can read individual alpha-numeric characters in almost any printed font and can form words from these characters. The words can then be used in data analysis by another computer system or by the instant character recognition system. Examples of such data analyses include sorting of products by product name, tabulating for automatic factory invoicing and verifying the print quality of date and lot codes.
In a preferred embodiment the present invention employs a pair of solid state TV cameras, a pair of interface/memory circuits (also known as "framegrabbers"), a pair of TV monitors, a computer, a keyboard, a joystick and strobe lights. In the system software are stored "menus" which guide the operator in the use of the system. These menus and the manner in which they are presented render the system very user-friendly.
The basic steps of the character recognition process of the present invention are set forth below. These steps are used both in "teaching" a known character to the system, in the course of building up a character library, and in "reading" an unknown character and attempting to match the unknown character with a known character stored in the library. The basic process steps are set forth below:
1. Acquire an image from the TV camera using a framegrabber.
2. Define a window search area using the joystick to move a cursor on the TV monitor.
3. Search for a character by scanning the search window to locate the left, right, top and bottom most points of the character.
4. Determine the character width and height in terms of pixels, each pixel having a grey scale value.
5. Calculate the number of pixels per dot required to fit the character into a dot matrix, distributing any extra pixels uniformly among the dots.
6. Calculate a single grey scale value for each of the dots in the dot matrix by combining the values for the pixels associated with each dot.
7. Generate a grey scale histogram using the newly calculated grey scale values for the dots in the dot matrix.
8. Determine a grey scale threshhold for the dots in the dot matrix.
9. Convert each dot data point from its grey scale value to a binary value.